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UPS 6000 and UP Xtreme i11 Robot Kits
Create Your Own Robot Kit
Perception
Navigation
Simulation
Benchmarking and Profiling
EI for AMR Container on a Virtual Machine
Fibocom’s FM350 5G Module Integration
Change Existing and Add New Docker* Images to the EI for AMR SDK
Troubleshooting for Robot Tutorials
Spatial Partitioning and Search Operations with Octrees
Constructing a Convex Hull Polygon for a 3D Point Cloud
Detecting Specific Models and Their Parameters in 3D Point Clouds
Plane Model Segmentation
Surface Reconstruction with Intel® oneAPI Base Toolkit's Moving Least Squares (MLS)
Intel® oneAPI Base Toolkit's Iterative Closest Point (ICP)
KdTree Search Using Intel® oneAPI Base Toolkit's KdTree FLANN
Downsampling 3D Point Clouds with a Voxelized Grid
Filtering Point Clouds with a Passthrough Filter
PCL Optimizations Outside of Docker* Images
Optimized PCL Known Limitation
Optimized PCL Troubleshooting
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Wandering Application in a ARIAC Gazebo* Simulation
This tutorial tells you how to use an industrial simulation room model (the OSRF GEAR workcell that was used for the 2018 ARIAC competition) with objects and a wafflebot3 robot for simulation in Gazebo*. The industrial room includes: shelves, conveyor belts, pallets, boxes, robots, stairs, ground lane markers, and a tiled boundary wall.
Run the Sample Application
If your system has an Intel® GPU, follow the steps in the Get Started Guide for Robots to enable the GPU for simulation. This step improves Gazebo* simulation performance.
Check if your installation has the turtlesim Docker* image.
docker images |egrep "amr-turtlebot3|amr-rtabmap|amr-nav2|amr-wandering" #if you have them installed, the result is: amr-turtlesim amr-rtabmap amr-nav2 wandering
NOTE:If one or more of the images are not installed, continuing with these steps triggers a build that takes longer than an hour (sometimes, a lot longer depending on the system resources and internet connection).If one or more of the images are not installed, Intel recommends installing the Robot Complete Kit with the Get Started Guide for Robots.
Go to the AMR_containers folder:
cd <edge_insights_for_amr_path>/Edge_Insights_for_Autonomous_Mobile_Robots_<version>/AMR_containers
Prepare the environment setup:
source ./01_docker_sdk_env/docker_compose/common/docker_compose.source export CONTAINER_BASE_PATH=`pwd` export ROS_DOMAIN_ID=32
Run the command below to start the Docker* container:
CHOOSE_USER=eiforamr docker-compose -f 01_docker_sdk_env/docker_compose/05_tutorials/wandering_gazebo_ariac.tutorial.yml up
Expected output:
The robot starts wandering inside the simulation. See the simulation snapshots from different angles:
To increase performance, the real time update rate can be set to 0:
In Gazebo*’s left panel, go to the World Tab, and click Physics.
Change the real time update rate to 0.
To close this, do one of the following:
Type Ctrl-c in the terminal where you did the up command.
Run this command in another terminal:
CHOOSE_USER=eiforamr docker-compose -f 01_docker_sdk_env/docker_compose/05_tutorials/wandering_gazebo_ariac.tutorial.yml down --remove-orphans
Troubleshooting
If the robot is not moving but Gazebo* is started, start the Wandering application manually by opening a container shell and entering:
The ARIAC world tutorial works only with the eiforamr user. If the yml is started with a different user, the Gazebo* model fails.
docker-compose -f 01_docker_sdk_env/docker_compose/01_amr/amr-sdk.all.yml run wandering bash ros2 run wandering_app wandering
For general robot issues, go to: Troubleshooting for Robot Tutorials.
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